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# Ultralytics YOLO 🚀, GPL-3.0 license
from ultralytics.yolo.utils.torch_utils import get_flops, get_num_params
try:
import comet_ml
except (ModuleNotFoundError, ImportError):
comet_ml = None
def on_pretrain_routine_start(trainer):
experiment = comet_ml.Experiment(project_name=trainer.args.project or "YOLOv8",)
experiment.log_parameters(dict(trainer.args))
def on_train_epoch_end(trainer):
experiment = comet_ml.get_global_experiment()
experiment.log_metrics(trainer.label_loss_items(trainer.tloss, prefix="train"), step=trainer.epoch + 1)
if trainer.epoch == 1:
for f in trainer.save_dir.glob('train_batch*.jpg'):
experiment.log_image(f, name=f.stem, step=trainer.epoch + 1)
def on_fit_epoch_end(trainer):
experiment = comet_ml.get_global_experiment()
experiment.log_metrics(trainer.metrics, step=trainer.epoch + 1)
if trainer.epoch == 0:
model_info = {
"model/parameters": get_num_params(trainer.model),
"model/GFLOPs": round(get_flops(trainer.model), 3),
"model/speed(ms)": round(trainer.validator.speed[1], 3)}
experiment.log_metrics(model_info, step=trainer.epoch + 1)
def on_train_end(trainer):
experiment = comet_ml.get_global_experiment()
experiment.log_model("YOLOv8", file_or_folder=trainer.best, file_name="best.pt", overwrite=True)
callbacks = {
"on_pretrain_routine_start": on_pretrain_routine_start,
"on_train_epoch_end": on_train_epoch_end,
"on_fit_epoch_end": on_fit_epoch_end,
"on_train_end": on_train_end} if comet_ml else {}
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